Burkholderia cepacia complex epidemiology in persons with cystic fibrosis from Australia and New Zealand

The Burkholderia cepacia complex (Bcc) is a group of significant opportunistic respiratory pathogens which affect people with cystic fibrosis. In this study, we sought to ascertain the epidemiology and geographic species distribution of 116 Bcc isolates collected from people with CF in Australia and New Zealand. We performed a combination of recA-based PCR, amplified rDNA restriction analysis (ARDRA), pulsed-field gel electrophoresis and repetitive extragenic palindromic PCR on each isolate. Each Burkholderia cenocepacia isolate was also screened by PCR for the presence of the B. cepacia epidemic strain marker. One hundred and fourteen isolates were assigned to a species using recA-based PCR and ARDRA. B. cenocepacia, B. multivorans and B. cepacia accounted for 45.7%, 29.3% and 11.2% of the isolates, respectively. Strain analysis of B. cenocepacia revealed that 85.3% of the isolates were unrelated. One related B. cenocepacia strain was identified amongst 15 people. Whilst full details of person-to-person contact was not available, all patients attended CF centres in Queensland (Qld) and New South Wales (NSW). Although person-to-person transmission of B. cenocepacia strains has occurred in Australia, the majority of CF-related Bcc infections in Australia and New Zealand are most likely acquired from the environment.

On the Security of Cognitive Radio Networks

Cognitive radio has emerged as an essential recipe for future high-capacity high-coverage multi-tier hierarchical networks. Securing data transmission in these networks is of utmost importance. In this paper, we consider the cognitive wiretap channel and propose multiple antennas to secure the transmission at the physical layer, where the eavesdropper overhears the transmission from the secondary transmitter to the secondary receiver. The secondary receiver and the eavesdropper are equipped with multiple antennas, and passive eavesdropping is considered where the channel state information of the eavesdropper’s channel is not available at the secondary transmitter. We present new closedform expressions for the exact and asymptotic secrecy outage probability. Our results reveal the impact of the primary network on the secondary network in the presence of a multi-antenna wiretap channel.

A quality-scalable and energy-efficient approach for spectral analysis of heart rate variability

Today there is a growing interest in the integration of health monitoring applications in portable devices necessitating the development of methods that improve the energy efficiency of such systems. In this paper, we present a systematic approach that enables energy-quality trade-offs in spectral analysis systems for bio-signals, which are useful in monitoring various health conditions as those associated with the heart-rate. To enable such trade-offs, the processed signals are expressed initially in a basis in which significant components that carry most of the relevant information can be easily distinguished from the parts that influence the output to a lesser extent. Such a classification allows the pruning of operations associated with the less significant signal components leading to power savings with minor quality loss since only less useful parts are pruned under the given requirements. To exploit the attributes of the modified spectral analysis system, thresholding rules are determined and adopted at design- and run-time, allowing the static or dynamic pruning of less-useful operations based on the accuracy and energy requirements. The proposed algorithm is implemented on a typical sensor node simulator and results show up-to 82% energy savings when static pruning is combined with voltage and frequency scaling, compared to the conventional algorithm in which such trade-offs were not available. In addition, experiments with numerous cardiac samples of various patients show that such energy savings come with a 4.9% average accuracy loss, which does not affect the system detection capability of sinus-arrhythmia which was used as a test case. 

Evidential Fusion for Gender Profiling

Gender profiling is a fundamental task that helps CCTV systems to
provide better service for intelligent surveillance. Since subjects being detected
by CCTVs are not always cooperative, a few profiling algorithms are proposed
to deal with situations when faces of subjects are not available, among which
the most common approach is to analyze subjects’ body shape information. In
addition, there are some drawbacks for normal profiling algorithms considered
in real applications. First, the profiling result is always uncertain. Second, for a
time-lasting gender profiling algorithm, the result is not stable. The degree of
certainty usually varies, sometimes even to the extent that a male is classified
as a female, and vice versa. These facets are studied in a recent paper [16] using
Dempster-Shafer theory. In particular, Denoeux’s cautious rule is applied for
fusion mass functions through time lines. However, this paper points out that if
severe mis-classification is happened at the beginning of the time line, the result
of applying Denoeux’s rule could be disastrous. To remedy this weakness,
in this paper, we propose two generalizations to the DS approach proposed in
[16] that incorporates time-window and time-attenuation, respectively, in applying
Denoeux’s rule along with time lines, for which the DS approach is a special
case. Experiments show that these two generalizations do provide better results
than their predecessor when mis-classifications happen.

Caroline: A Search for the Source of Earth's Water

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Secure Transmission in MIMO Wiretap Channels Using General-Order Transmit Antenna Selection with Outdated CSI

In this paper, we propose general-order transmit antenna selection to enhance the secrecy performance of multiple-input–multiple-output multieavesdropper channels with outdated channel state information (CSI) at the transmitter. To evaluate the effect of the outdated CSI on the secure transmission of the system, we investigate the secrecy performance for two practical scenarios, i.e., Scenarios I and II, where the eavesdropper's CSI is not available at the transmitter and is available at the transmitter, respectively. For Scenario I, we derive exact and asymptotic closed-form expressions for the secrecy outage probability in Nakagami- m fading channels. In addition, we also derive the probability of nonzero secrecy capacity and the \varepsilon -outage secrecy capacity, respectively. Simple asymptotic expressions for the secrecy outage probability reveal that the secrecy diversity order is reduced when the CSI is outdated at the transmitter, and it is independent of the number of antennas at each eavesdropper N_text\rm{E} , the fading parameter of the eavesdropper's channel m_text\rm{E} , and the number of eavesdroppers M . For Scenario II, we make a comprehensive analysis of the average secrecy capacity obtained by the system. Specifically, new closed-form expressions for the exact and asymptotic average secrecy capacity are derived, which are valid for general systems with an arbitrary number of antennas, number of eavesdroppers, and fading severity parameters. Resorting to these results, we also determine a high signal-to-noise ratio power offset to explicitly quantify the impact of the main c- annel and the eavesdropper's channel on the average secrecy capacity.

The size distribution of Jupiter Family comets

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Towards Automated Data-Driven Model Creation for Cloud Computing Simulation

The increasing complexity and scale of cloud computing environments due to widespread data centre heterogeneity makes measurement-based evaluations highly difficult to achieve. Therefore the use of simulation tools to support decision making in cloud computing environments to cope with this problem is an increasing trend. However the data required in order to model cloud computing environments with an appropriate degree of accuracy is typically large, very difficult to collect without some form of automation, often not available in a suitable format and a time consuming process if done manually. In this research, an automated method for cloud computing topology definition, data collection and model creation activities is presented, within the context of a suite of tools that have been developed and integrated to support these activities.

PTEN mRNA detection by chromogenic, RNA in situ technologies: a reliable alternative to PTEN immunohistochemistry

Immunohistochemical staining for phosphatase and tensin homolog (PTEN) does not have either an acceptable standard protocol or concordance of scoring between pathologists. Evaluation of PTEN mRNA with a unique and verified sequence probe may offer a realistic alternative providing a robust and reproducible protocol. In this study, we have evaluated an in situ hybridization (ISH) protocol for PTEN mRNA using RNAScope technology and compared it with a standard protocol for PTEN immunohistochemistry (IHC). PTEN mRNA expression by ISH was consistently more sensitive than PTEN IHC, with 56% of samples on a mixed-tumor tissue microarray (TMA) showing high expression by ISH compared with 42% by IHC. On a prostate TMA, 49% of cases showed high expression by ISH compared with 43% by IHC. Variations in PTEN mRNA expression within malignant epithelium were quantifiable using image analysis on the prostate TMAs. Within tumors, clear overexpression of PTEN mRNA on malignant epithelium compared with benign epithelium was frequently observed and quantified. The use of SpotStudio software in the mixed-tumor TMA allowed for clear demonstration of varying levels of PTEN mRNA between tumor samples by the mRNA methodology. This was evident by the quantifiable differences between distinct oropharyngeal tumors (up to 3-fold increase in average number of spots per cell between 2 cases). mRNA detection of PTEN or other biomarkers, for which optimal or standardized immunohistochemical techniques are not available, represents a means by which heterogeneity of expression within focal regions of tumor can be explored with more confidence.

Whole Genome Sequencing Reveals Local Transmission Patterns of Mycobacterium bovis in Sympatric Cattle and Badger Populations

Whole genome sequencing (WGS) technology holds great promise as a tool for the forensic epidemiology of bacterial pathogens. It is likely to be particularly useful for studying the transmission dynamics of an observed epidemic involving a largely unsampled 'reservoir' host, as for bovine tuberculosis (bTB) in British and Irish cattle and badgers. BTB is caused by Mycobacterium bovis, a member of the M. tuberculosis complex that also includes the aetiological agent for human TB. In this study, we identified a spatio-temporally linked group of 26 cattle and 4 badgers infected with the same Variable Number Tandem Repeat (VNTR) type of M. bovis. Single-nucleotide polymorphisms (SNPs) between sequences identified differences that were consistent with bacterial lineages being persistent on or near farms for several years, despite multiple clear whole herd tests in the interim. Comparing WGS data to mathematical models showed good correlations between genetic divergence and spatial distance, but poor correspondence to the network of cattle movements or within-herd contacts. Badger isolates showed between zero and four SNP differences from the nearest cattle isolate, providing evidence for recent transmissions between the two hosts. This is the first direct genetic evidence of M. bovis persistence on farms over multiple outbreaks with a continued, ongoing interaction with local badgers. However, despite unprecedented resolution, directionality of transmission cannot be inferred at this stage. Despite the often notoriously long timescales between time of infection and time of sampling for TB, our results suggest that WGS data alone can provide insights into TB epidemiology even where detailed contact data are not available, and that more extensive sampling and analysis will allow for quantification of the extent and direction of transmission between cattle and badgers. © 2012 Biek et al.

Availability and transfer to grain of As, Cd, Cu, Ni, Pb and Zn in a barley agri-system: Impact of biochar, organic and mineral fertilizers

With biochar becoming an emerging soil amendment and a tool to mitigate climate change, there are only a few studies documenting its effects on trace element cycling in agriculture. Zn and Cu are deficient in many human diets, whilst exposures to As, Pb and Cd need to be decreased. Biochar has been shown to affect many of them mainly at a bench or greenhouse scale, but field research is not available. In our experiment we studied the impact of biochar, as well as its interactions with organic (compost and sewage sludge) and mineral fertilisers (NPK and nitrosulfate), on trace element mobility in a Mediterranean agricultural field (east of Madrid, Spain) cropped with barley. At harvesting time, we analysed the soluble fraction, the available fraction (assessed with the diffusive gradients in thin gels technique, DGT) and the concentration of trace elements in barley grain. No treatment was able to significantly increase Zn, Cu or Ni concentration in barley grain, limiting the application for cereal fortification. Biochar helped to reduce Cd and Pb in grain, whereas As concentration slightly increased. Overall biochar amendments demonstrated a potential to decrease Cd uptake in cereals, a substantial pathway of exposure in the Spanish population, whereas mineral fertilisation and sewage sludge increased grain Cd and Pb. In the soil, biochar helped to stabilise Pb and Cd, while marginally increasing As release/mobilisation. Some of the fertilisation practises or treatments increased toxic metals and As solubility in soil, but never to an extent high enough to be considered an environmental risk. Future research may try to fortify Zn, Cu and Ni using other combinations of organic amendments and different parent biomass to produce enriched biochars.